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Joseph Futoma
Person information
- affiliation: Apple, New York, NY, USA
- affiliation (former): Harvard University, Paulson School of Engineering and Applied Sciences, Cambridge, MA, USA
- affiliation (former, PhD 2018): Duke University, Department of Statistical Science, Durham, NC, USA
- affiliation (former): Dartmouth College, Department of Mathematics, Hanover, NH, USA
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2020 – today
- 2021
- [j2]Sean Jewell, Joseph Futoma, Lauren Hannah, Andrew C. Miller, Nicholas J. Foti, Emily B. Fox:
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. npj Digit. Medicine 4 (2021) - [c10]Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox:
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. MLHC 2021: 308-336 - [i7]Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox:
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. CoRR abs/2104.12231 (2021) - 2020
- [c9]Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez:
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning. AISTATS 2020: 3578-3588 - [c8]Mark P. Sendak, Madeleine Clare Elish, Michael Gao, Joseph Futoma, William Ratliff, Marshall Nichols, Armando Bedoya, Suresh Balu, Cara O'Brien:
"The human body is a black box": supporting clinical decision-making with deep learning. FAT* 2020: 99-109 - [c7]Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez:
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. ICML 2020: 3658-3667 - [c6]Jianzhun Du, Joseph Futoma, Finale Doshi-Velez:
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. NeurIPS 2020 - [i6]Joseph Futoma, Muhammad A. Masood, Finale Doshi-Velez:
Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning. CoRR abs/2001.03224 (2020) - [i5]Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez:
POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning. CoRR abs/2001.04032 (2020) - [i4]Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez:
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. CoRR abs/2002.03478 (2020) - [i3]Jianzhun Du, Joseph Futoma, Finale Doshi-Velez:
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. CoRR abs/2006.16210 (2020)
2010 – 2019
- 2019
- [i2]Mark P. Sendak, Madeleine Clare Elish, Michael Gao, Joseph Futoma, William Ratliff, Marshall Nichols, Armando Bedoya, Suresh Balu, Cara O'Brien:
"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning. CoRR abs/1911.08089 (2019) - 2018
- [b1]Joseph Futoma:
Gaussian Process-Based Models for Clinical Time Series in Healthcare. Duke University, Durham, NC, USA, 2018 - 2017
- [c5]Joseph Futoma, Sanjay Hariharan, Katherine A. Heller:
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier. ICML 2017: 1174-1182 - [c4]Joseph Futoma, Sanjay Hariharan, Katherine A. Heller, Mark P. Sendak, Nathan Brajer, Meredith Clement, Armando Bedoya, Cara O'Brien:
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection. MLHC 2017: 243-254 - 2016
- [c3]Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller:
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data. MLHC 2016: 42-54 - [c2]Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller:
Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease. UAI 2016 - 2015
- [j1]Joseph Futoma, Jonathan Morris, Joseph Lucas:
A comparison of models for predicting early hospital readmissions. J. Biomed. Informatics 56: 229-238 (2015) - 2013
- [c1]Nicholas J. Foti, Joseph D. Futoma, Daniel N. Rockmore, Sinead Williamson:
A unifying representation for a class of dependent random measures. AISTATS 2013: 20-28 - 2012
- [i1]Nicholas J. Foti, Joseph D. Futoma, Daniel N. Rockmore, Sinead Williamson:
A unifying representation for a class of dependent random measures. CoRR abs/1211.4753 (2012)
Coauthor Index
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